1. Field
This disclosure relates to a system for performing video content analysis (VCA) using depth information to assist monitoring building occupancy and/or usage.
2. Background
Use of video to monitor building occupancy and usage by the occupants can be very helpful. Video can be reviewed in real time, or later after storage, for a variety of purposes, such as security, energy efficiency and convenience to the building occupant. However, monitoring videos by a person may not be practicable for many applications. To assist in reviewing video, video content analysis systems have been designed. In a video content analysis (VCA) system, video streams are automatically analyzed to identify and classify objects, and to determine physical and temporal attributes of the objects. As a result, a log of analytics data may be stored. The analytics data may be used to determine events that occur in real time or at a later time, to aid in searching for objects or detected events, and for other purposes. An example of a VCA system is described in U.S. Pat. No. 7,932,923, issued to Lipton et al. on Apr. 26, 2011 (the '923 patent) and as well in U.S. Pat. No. 7,868,912 issued to Venetianer et al. on Mar. 11, 2011, the contents of each of which are incorporated herein by reference in their entirety.
Some existing systems use RGB (red green blue) or other image sensors that sense images in a two-dimensional manner and perform analysis of those images to perform object and event detection. However, identifying objects and related actions using RGB image sensors may be prone to error. For example, a VCA system may make a determination that an object is a human based on an analysis of the shape of the detected object (e.g., the detected object has a certain shape, such as a particular size relationship of a detected torso, head and arm/leg appendages). However, such analysis to determine that an object is a human may equally apply to the shadow of a human in a building. (As used in this disclosure, a “building” refers to both commercial buildings (e.g., office buildings, warehouses, etc.) as well as residential houses and other buildings). If the VCA system is interested in determining occupancy of a building or usages of or within the building, inaccurate detection of people and/or their actions may result in undesirable actions or inactions. For example, if a system is designed to turn off lights when no one in a certain location of a building is detected, an inaccurate assessment of an object as not a person may result in lights being turned off at the location even when a person is present, possibly creating a dangerous situation. Conversely, if a system is designed to provide energy efficient heating and cooling if a low number of people are detected to be present, inaccurate detection of shadows and/or reflections as people may cause the system to provide inefficient heating and cooling, creating waste and higher usage costs of the building.
The embodiments described here address some of these problems of existing building monitoring systems, and provide use of depth and/or height data to assist in monitoring a buildings and their usage. As a result, a more accurate system and method for detecting and tracking building occupants and their actions may be achieved.